Genome classification improvements based on k-mer intervals in sequences

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Given the vast amount of genomic data, alignment-free sequence comparison methods are required due to their low computational complexity. k-mer based methods can improve comparison accuracy by extracting an effective feature of the genome sequences. The aim of this paper is to extract k-mer intervals of a sequence as a feature of a genome for high comparison accuracy. In the proposed method, we calculated the distance between genome sequences by comparing the distribution of k-mer intervals. Then, we identified the classification results using phylogenetic trees. We used viral, mitochondrial (MT), microbial and mammalian genome sequences to perform classification for various genome sets. We confirmed that the proposed method provides a better classification result than other k-mer based methods. Furthermore, the proposed method could efficiently be applied to long sequences such as human and mouse genomes.
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
Issue Date
2019-12
Language
English
Article Type
Article
Citation

GENOMICS, v.111, no.6, pp.1574 - 1582

ISSN
0888-7543
DOI
10.1016/j.ygeno.2018.11.001
URI
http://hdl.handle.net/10203/268806
Appears in Collection
EE-Journal Papers(저널논문)
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